Machine learning approaches to cryoEM density modification differentially affect biomacromolecule and ligand density quality.
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| Title: | Machine learning approaches to cryoEM density modification differentially affect biomacromolecule and ligand density quality. |
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| Authors: | Berkeley RF; Department of Chemistry and Biochemistry, University of California San Diego, La Jolla, CA, United States., Cook BD; Department of Chemistry and Biochemistry, University of California San Diego, La Jolla, CA, United States., Herzik MA Jr; Department of Chemistry and Biochemistry, University of California San Diego, La Jolla, CA, United States. |
| Source: | Frontiers in molecular biosciences [Front Mol Biosci] 2024 Apr 18; Vol. 11, pp. 1404885. Date of Electronic Publication: 2024 Apr 18 (Print Publication: 2024). |
| Publication Type: | Journal Article |
| Journal Info: | Publisher: Frontiers Media S.A Country of Publication: Switzerland NLM ID: 101653173 Publication Model: eCollection Cited Medium: Print ISSN: 2296-889X (Print) Linking ISSN: 2296889X NLM ISO Abbreviation: Front Mol Biosci Subsets: PubMed not MEDLINE |
| Database: | MEDLINE Ultimate |
| ISSN: | 2296-889X |
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| DOI: | 10.3389/fmolb.2024.1404885 |
